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• 영문명: Prediction of Physical Examination Demand Using Text Mining
• 발행기관: 한국IT서비스학회
• 저자명: 박경보 김미량
• 간행물 정보: 『한국IT서비스학회지』제21권 제5호, 95~106쪽, 전체 12쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2022.10.31

영문 초록

Recently, physical examinations have become an important strategy to reduce costs for individuals and society. Pre-physical counseling is important for an effective physical examination. However, incomplete counseling is being conducted because the demand for physical examinations is not predicted. Therefore, in this study, the demand for physical examination was predicted using text mining and stepwise regression. As a result of the analysis, the most recent text data showed a high explanatory power of the demand for physical examination. Also, large amounts of data have high explanatory power. In addition, it was found that the high frequency of the text “health food” reduces the number of health examination customers. And the higher the frequency of the text of the word “food”, the lower the number of physical examination customers. However, when the word “wild ginseng” was exposed a lot on Twitter, the number of physical examination customers visiting hospitals increased. In other words, customers consume efficiently by comparing the health examination price with the price of consumer goods. The proposed research framework can help predict demand in other industries.

목차

1. 서론

2. 선행 연구

3. 연구 방법

4. 연구 결과

5. 결론

참고문헌

키워드

Physical Examination Text Mining Demand Forecast Stepwise Regression